help identify the root cause of the problem and the impact on accommodation of the population (Rajulu, 2010: Population Analysis). Take as an example an individual seated in a chair. The analytical analysis and CAD modeling both indicate that all subjects should be accommodated within the seat; however, during HITL testing one female subject complains that the edge of the seat pan is painfully digging into the back of her knee. On subsequent percentile analysis you determine that she has a 20th -percentile female buttock-to-popliteal length and has the smallest value of all subjects in the HITL test. This indicates that women ranging from the 1st to the 20th percentile may have a similar issue with the edge of the seat pan. Perhaps the impingement is caused by postural differences between small women and the rest of the population, perhaps the ability to conform to the seat pan is different for smaller women, or perhaps the foot rest adjustability dropped the thigh closer than ideal to the seat pan. Regardless, a segment of the population is now identified as “at risk,” a designation that requires further follow-up and analysis.
The third goal of the HITL data analysis is to classify whether the worst-case scenarios pass or fail the anthropometric requirements, by extrapolating from HITL test subjects who may not be the worst cases from both an accommodation and performance perspective. In the ideal situation, where the subjects tested in the HITL study have no observed issues with clearance or restrictions with the interface, the subjects must still be classified in terms of the overall population using percentiles. The basis for this classification is to determine the human-to-hardware clearance values, and extrapolate to determine whether individuals who were identified as the “worst cases” of that
measurement will have an issue. As an example of an extrapolation population analysis scenario, consider the task of walking through an entryway while wearing a suit.
Hypothetically speaking, the critical dimensions of interest would be identified as bideltoid breadth and stature, and the 2 worst-case scenarios would be the largest values (i.e., 99th-percentile male in both bideltoid breadth and stature). Before testing, the scenario is analytically examined and the entryway seems to accommodate a suited 99th-percentile male in both bideltoid breadth and stature, but it is not yet verified as meeting the requirements at this stage. The motion of walking involves 2 aspects that must be accounted for in the population analysis: a swinging motion of the arms, resulting in a higher width requirement, and the height variations observed during walking, which may increase the amount of head clearance required. For this example, a group of subjects ranges from 20th- to 80th-percentile male bideltoid breadth and 60th- to 95th-percentile male stature. During testing, all subjects were able to walk through the door, but the total clearance was only about 2 inches for the men who had the largest bideltoid breadth and 1 inch for stature. Collecting unsuited data from the subject pool and comparing each subject’s values and the actual observed clearance will cause the analysis to yield the anticipated postural effects (see paragraph 4.5.2.5.3.2 Postural Factors). By extrapolating the observed postural effects to the 99th-percentile male values for both dimensions, designers can determine the required entryway dimensions and compare them to the actual mockup or design. As a result, this hypothetical
population analysis identifies the necessary requirements the design must meet, given the worst-case scenario for this selected task.
The HITL test will be used to examine the worst-case manikins identified from the analytical analysis and CAD modeling, validate the assumptions from the previous analysis, and identify any unforeseen issues in the design. If the previous analysis assumptions are determined to be incorrect, the analytical analysis and CAD modeling must be re-run with the updated assumptions in place to evaluate compliance of the design. If the design is determined to be noncompliant with the anthropometric
requirements, the issues must be mitigated by making appropriate design changes. If changes are made, the analytical analysis and CAD modeling should be re-run to ensure that a different segment of the population is not affected by the modified design.
Finally, if the design is compliant according to the HITL test, designers should continue conducting HITL testing using mockups at a higher fidelity level until the final stage of design is reached. Strategically placed iterative HITL tests will ensure that differences between the low-fidelity and high-fidelity stages of the design will not result in
accommodation issues and that seemingly minor changes to a design will not result in major issues in the end product.
This iterative process results in an optimized methodology, in which the HITL test is used to validate design assumptions and identify problem areas, the modeling and analytical analyses are used to explore those problems, evaluate the population, and make design changes, and the process repeats until a design is ready for the prototype stage. By not relying solely on one method, a designer can ensure that the entire
population is both mathematically and functionally accommodated within the complexity of the overall human-systems interface while validating the assumptions by using actual human data.
Additional discussion of HITL testing for anthropometry, biomechanics, and strength assessments can be found in HIDH section 4.2.4.2 Enhancement of Human-in-the-Loop Testing.
4.5.2.6.4 PERCENTILE ANALYSIS
Percentile analysis can be used at all levels of analytical, modeling, and HITL analyses.
In the most simplistic terms, anthropometric verification and validation is a comparison of the design against the maximum and minimum critical dimensions. As the complexity of the analysis increases, the percentile analysis becomes a critical tool for evaluation of the design. As discussed throughout this section, the selected anthropometric data set in conjunction with percentiles can be used to derive atypical measurements, and evaluate multivariate posture-based body configurations and group effects. The percentile analysis can be used to place the design constraints in the context of the population, evaluate HITL subjects in relation to worst-case subjects, assist with extrapolation of the results to the worst cases, and even yield the accommodation restrictions of the design. It is highly recommended that designers use this tool during the design process, using the basic mathematical equation (Equation 2) or using the more complex variations, adding in the microgravity aspect (Equation 1) or the suited aspect (Margerum, 2008: Case Study #2) to assist with validation and verification of the design.
4.5.2.6.5 USE OF THE MINIMUM AND MAXIMUM POPULATION ACCOMMODATION VALUES
A design may not specifically require both the maximum and minimum values, but care must be taken to account for both of them in the context of the overall vehicle design.
Both the maximum and minimum values must be considered even if a design
specifically uses only one of the critical values. Using a basic seat example, the seat pan width must meet the maximum hip breadth value to ensure that all crewmembers are supported, but examination of the minimum should be considered in terms of crew safety or comfort. If the crew is jostled on launch and landing, the smaller women may shift around on the seat plan, which could cause discomfort and potential injury. Thus, although the seat pan width is driven by the maximum and supports the entire
population range, a factor of adjustability for that dimension is driven by the combination of the maximum and minimum. Consideration of this adjustability factor is essential for crew comfort and safety.
4.5.2.7 ANTHROPOMETRY TECHNICAL PRODUCTS
Verification and validation of a given design requires that the entire population range is accounted for in the design. At a minimum, the design must meet the relevant maximum and minimum ranges for the selected set of critical dimensions set forth by Requirement V2 4003 and tied to the data set used for satisfaction of V2 4001. The design must prove through analytical, modeling, and HITL methods that the entire population spectrum between the maximum and minimum values has been accounted for within the design. Designs in which multiple critical dimensions interact, such as posture- based clearance measurements, must use the relevant analysis methods to
accommodate the population as a whole. Successful verification for these multi-variable scenarios would mean that the design accounts for the entire range between the
minimum and maximum values for the given measurements of interest using the entire selected anthropometric data set.
For each of the major milestones of the design life cycle, the technical products in Table 4.5.2.7-1 are recommended for review by the NASA customer.
TABLE 4.5.2.7-1 ANTHROPOMETRY TECHNICAL PRODUCTS
Technical Products
A description of the ConOps, function allocation, associated crew task lists, and the selected anthropometric data set and its associated critical measurement ranges. Includes list of tasks considered to be design-driving for anthropometry requirements as well as definition of factors influencing anthropometry.
I U U U --- ---
A summary of modeling/analysis/evaluation (i.e., CAD, human modeling, and population analysis) performed to date and the influence on system design with links to the detailed analysis results.
Required per NPR 8705.2B, and HITL evaluations required per paragraph 2.3.10.
--- --- I U U ---
System architecture drawings (structures,
equipment, etc.), material specifications, interface requirements.
Concept of Operations and Crew Task Lists
The ConOps, described in paragraph 3.2.3.1.2, provides information such as
identification of crew activities and determination of which subsystems are affected by crew activities. Function allocation, described in paragraph 3.2.3.1.3, establishes the extent to which an activity is to be automated or assigned to humans. The crew task list, described in section 4.1 User Task Analysis, documents details including allocation of function between crew and systems, definition of the sequence of crew activities, and identification of critical tasks. As the crew task list evolves through the design cycle, its final iteration should become crew procedures.
For anthropometry requirements, it is important to determine what tasks may be design-driving. Tasks or uses of hardware that represent challenges for anthropometric
extremes will be particularly important for system-level analysis and testing. Factors that may influence anthropometry include suit conditions, posture, gravity conditions, and group effects.
Modeling, Analysis, and Evaluation Summaries
Iterative summaries of modeling, analyses, and evaluations provide NASA with insight into technical details of human-systems integration throughout the design process. As designs mature, modeling, analyses, and evaluations should use inputs and mockups of increasingly higher fidelity, as discussed in paragraph 3.2.3.3 Evaluate Designs and Iterate Solutions. It is important that summaries address how key and critical design decisions were assessed. According to the NPR 8705.2B, updated summaries are to be provided at each design review through SAR. Also, in paragraph 2.3.10, the use of HITL evaluation is a required method to progressively demonstrate that the operational
concept meets system requirements for operational safety, efficiency, and user interface design.
For anthropometric analyses, as appropriate for each design phase, reports should detail CAD model work and progressively higher fidelity human model work in addition to analysis of HITL evaluations. Population analysis ensures that findings extend to the entire crew population and consider worst-case scenarios.
Architecture, Materials, and Interface Specifications
Drawings, materials, and interface specifications provide NASA with insight into human-systems integration technical details throughout the design process.
Verification Plan
The verification plan is a formal document describing the specific methodologies to be used to show compliance with each requirement.
System Requirements Review (SRR) Suggested developer technical products:
Selected anthropometric data set and its associated critical measurement ranges
Overall plan for meeting anthropometric design compliance
Definition of human-related major systems and what anthropometric requirements are applicable
High-level analytical analyses examining the impact of anthropometric requirements on the design
Plans for mitigation efforts if high-level analyses indicate that design does not meet requirements
NASA Involvement:
Review overall plan, give feedback
Review major systems and applicable requirements, give feedback
Review analytical analysis results for consistency and methodology and plans for mitigation, give feedback
System Definition Review (SDR)
Suggested developer technical products:
Reports detailing analytical analyses for all major subsystems, to prove that concept designs meet anthropometric requirements and account for assumptions
If available, reports detailing preliminary CAD model work based on previous analytical analyses to prove that concept designs meet anthropometric requirements and account for assumptions
Plans for mitigation efforts if analyses indicate that design does not meet requirements
NASA Involvement:
Review reports and mitigation plans, provide feedback Preliminary Design Review (PDR)
Suggested developer technical products:
Reports on detailed analyses (analytical, modeling, and HITL) examining the impact of anthropometric requirements on the human-systems interface design, with any limitations and assumptions addressed
Plans for mitigation efforts if analyses indicate that design does not meet requirements
Plan for verification of requirements NASA Involvement:
Review detailed analysis results for consistency and methodology, provide feedback
Review plans, provide feedback Critical Design Review (CDR)
Suggested developer technical products:
Reports detailing HITL testing to examine the impact of anthropometric
requirements on the design; plans for mitigation efforts if analyses indicate that design does not meet requirements
Reports on updated analyses (analytical and modeling) based on results of HITL testing to examine the impact of anthropometric requirements on the human-systems interface design; plans for mitigation efforts if analyses indicate that design does not meet requirements
Final plans for anthropometric verification testing NASA Involvement:
Review reports, provide feedback
Review verification plan, provide feedback
Review design for consistency and methodology, provide feedback on final prototype design
Test Readiness Review (TRR)
Suggested developer technical products:
Demonstration of adherence to overall plan for meeting human-systems design compliance and justification for necessary plan changes
All testing completed and mitigation efforts incorporated into the design
NASA Involvement:
Review report, give feedback System Acceptance Review (SAR)
Suggested developer Company technical products:
Demonstration of design compliance and all anthropometric requirements met NASA Involvement:
Review of design relative to levied anthropometric requirements
4.5.2.8 ANTHROPOMETRY REFERENCES
Churchill, E. & McConville, J. (1976). Sampling and data gathering strategies for future USAF anthropometry, Appendix II-A. Air Force Systems Command, Wright Patterson Air Force Base, OH.
Gonzalez, L. J., & Rajulu, S. L. (2003, June) Posture-based whole body anthropometric analysis – A case study, Paper presented at the meeting Digital Human Modeling for Design and Engineering Conference and Exhibition, Montreal, Canada.
Gordon, C. C., Bradtmiller, B., Churchill, T., Clauser, C. E., McConville, J. T., Tebbetts.
I., & Walker, R. A. (1989, September). 1988 Anthropometric Survey of U.S. Army Personnel (ANSUR): Methods and summary statistics (NATICK/TR-89/044). Natick, MA: U.S. Army Natick RD&E Center.
Margerum, S., & Rajulu, S. (2008). Human factors analysis of crew height and weight limitations in space vehicle design. Human Factors and Ergonomics Society Annual Meeting Proceedings, 52(1), 114-118.
McConville, J., & Tillman, B. (1991). Year 2015 astronaut population anthropometric calculations for NASA-STD-3000. Houston, TX: Johnson Space Center.
U.S. Department of Health and Human Services. (2004, October). NHANES (National Health and Nutrition Examination Survey) Mean Body Weight, Height, and Body Mass Index, United States 1960–2002. Rockville, MD: Author.
Rajulu, S., Margerum, S., Young, K., & Blackledge, C. (2010). Anthropometric
processes for population analysis, suit factor generation, and a NASA recommended set of practices essential for data collection and analysis for verification and validation of vehicle, suit, and vehicle-suit interface requirements. (JSC 65851). Houston, TX:
Johnson Space Center.
Thaxton, S., & Rajulu, S. (2008). Population analysis: Communicating about
anthropometry in context. Human Factors and Ergonomics Society Annual Meeting Proceedings, 52(1), 119-123(5).
4.5.3 DESIGN FOR RANGE OF MOTION 4.5.3.1 INTRODUCTION
The NASA-STD-3001, Volume 2 NASA Spaceflight Human-System Standard, section 4 Physical Characteristics and Capabilities, includes requirements to accommodate crew ranges of motion (ROM) and reach. The purpose of mobility design requirements is to ensure that all developed hardware is operable by all potential NASA crewmembers.
Accordingly, all designers and developers of space systems will need to demonstrate compliance with the verification requirement using a variety of methodologies including analysis, modeling, and HITL testing.
4.5.3.2 APPLICABLE REQUIREMENTS
The following NASA-STD-3001, Volume 2 requirements are applicable to range of motion:
Data Sets [V2 4001]
Data Set Characteristics [V2 4002]
Population Definition [V2 4003]
Data Set Assumptions [V2 4004]
Range of Motion Data [V2 4007]
Reach Data [V2 4008]
4.5.3.3 SELECTION OF A RANGE-OF-MOTION DATA SET
The NASA-STD-3001 NASA Spaceflight Human-System Standard Requirement V2 4001 specifies that a biomechanics data set for the crewmember population must be selected and implemented in the design for range of motion (V2 4007) and reach (V2 4008) Requirement V2 4004 specifies that age, gender, and physical condition shall also be included in this data set. Furthermore, Requirement V2 4003 requires the definition of the population ranges for the physical dimensions that the system is intended to accommodate, and V2 4002 requires these values to include suited conditions.
ROM of a joint is measured by using the maximum observed angle of a joint during a specified task or posture. ROM is referenced in terms of rotation of a child entity with respect to a parent entity, and the exact rotation definitions depend on what type of coordinate system (e.g.., Cartesian, spherical) or transformation (e.g., Euler, fixed) is used by a program. Proper representation of the crewmember population with ROM for both unsuited and suited tasks can be done with a combination of literature surveys and data collection. No data set of ROM values is available as there is with anthropometry;
however, a variety of technical papers detail ROM values for particular tasks. The particular joints selected for each requirement would be those identified as important through a task analysis, for example, only upper body, only lower body, or entire body for certain tasks. If the program uses data collection to gather the ROM data, the limits
should be determined by using the minimum of the maximum ROM data of the test subject pool. Using information that is in the public domain and data collected from unsuited and suited subjects, a designer can determine the anticipated ROM of the population, as well as the impact of the suit on ROM values, using a crew task to drive the selection of the requirement limits. The ROM requirements specified in HSIR and CHSIR were determined through a study of tasks, specific to suited crewmembers, that focused on the functional ROM. The unsuited and suited motion data were compared across multiple subjects and were summarized first by task; then the tasks were compiled into an overall set of requirements delineated by joint.
4.5.3.4 RANGE OF MOTION GENERAL OVERVIEW
Unfortunately there is no single, simple test to verify that a design will meet mobility requirements for any crewmember. A systematic approach must be taken to conduct progressively more vigorous testing to ensure that a crewmember in the worst-case configuration (see section 4.5.3.5.2 ROM in the worst-case configuration) (e.g., restrained, seated, and suited at various gravitational states with a full contingent of crew in place) can still perform all required operations. Analytical and CAD-based
modeling may be implemented as a part of initial concept testing to identify key areas of concern. HITL testing may then be conducted with progressively higher fidelity
hardware and tests to ensure that all mobility requirements are met. Initial HITL testing may involve a single test subject in a low-fidelity hardware mockup at 1g. Final phases of testing should involve a full complement of test subjects in flight configuration
(including high-fidelity flight hardware and pressure suits, if planned), performing all required operations, and when feasible and appropriate, at simulated relevant
(including high-fidelity flight hardware and pressure suits, if planned), performing all required operations, and when feasible and appropriate, at simulated relevant